Simulating Spiking Neural P systems without delays using GPUs

We present in this paper our work regarding simulating a type of P system known as a spiking neural P system (SNP system) using graphics processing units (GPUs). GPUs, because of their architectural optimization for parallel computations, are well-suited for highly parallelizable problems. Due to the advent of general purpose GPU computing in recent years, GPUs are not limited to graphics and video processing alone, but include computationally intensive scientific and mathematical applications as well. Moreover P systems, including SNP systems, are inherently and maximally parallel computing models whose inspirations are taken from the functioning and dynamics of a living cell. In particular, SNP systems try to give a modest but formal representation of a special type of cell known as the neuron and their interactions with one another. The nature of SNP systems allowed their representation as matrices, which is a crucial step in simulating them on highly parallel devices such as GPUs. The highly parallel nature of SNP systems necessitate the use of hardware intended for parallel computations. The simulation algorithms, design considerations, and implementation are presented. Finally, simulation results, observations, and analyses using an SNP system that generates all numbers in $\mathbb N$ - {1} are discussed, as well as recommendations for future work.Comment: 19 pages in total, 4 figures, listings/algorithms, submitted at the 9th Brainstorming Week in Membrane Computing, University of Seville, Spai

Towards synthetic biological approaches to resource utilization on space missions.

This paper demonstrates the significant utility of deploying non-traditional biological techniques to harness available volatiles and waste resources on manned missions to explore the Moon and Mars. Compared with anticipated non-biological approaches, it is determined that for 916 day Martian missions: 205 days of high-quality methane and oxygen Mars bioproduction with Methanobacterium thermoautotrophicum can reduce the mass of a Martian fuel-manufacture plant by 56%; 496 days of biomass generation with Arthrospira platensis and Arthrospira maxima on Mars can decrease the shipped wet-food mixed-menu mass for a Mars stay and a one-way voyage by 38%; 202 days of Mars polyhydroxybutyrate synthesis with Cupriavidus necator can lower the shipped mass to three-dimensional print a 120 m(3) six-person habitat by 85% and a few days of acetaminophen production with engineered Synechocystis sp. PCC 6803 can completely replenish expired or irradiated stocks of the pharmaceutical, thereby providing independence from unmanned resupply spacecraft that take up to 210 days to arrive. Analogous outcomes are included for lunar missions. Because of the benign assumptions involved, the results provide a glimpse of the intriguing potential of 'space synthetic biology', and help focus related efforts for immediate, near-term impact

Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate

With the rise of social media as an important channel for the debate and discussion of public affairs, online social networks such as Twitter have become important platforms for public information and engagement by policy makers. To communicate effectively through Twitter, policy makers need to understand how influence and interest propagate within its network of users. In this chapter we use graph-theoretic methods to analyse the Twitter debate surrounding NHS Englands controversial care.data scheme. Directionality is a crucial feature of the Twitter social graph - information flows from the followed to the followers - but is often ignored in social network analyses; our methods are based on the behaviour of dynamic processes on the network and can be applied naturally to directed networks. We uncover robust communities of users and show that these communities reflect how information flows through the Twitter network. We are also able to classify users by their differing roles in directing the flow of information through the network. Our methods and results will be useful to policy makers who would like to use Twitter effectively as a communication medium

Movies Tags Extraction Using Deep Learning

Retrieving information from movies is becoming increasingly demanding due to the enormous amount of multimedia data generated each day. Not only it helps in efficient search, archiving and classification of movies, but is also instrumental in content censorship and recommendation systems. Extracting key information from a movie and summarizing it in a few tags which best describe the movie presents a dedicated challenge and requires an intelligent approach to automatically analyze the movie. In this paper, we formulate movies tags extraction problem as a machine learning classification problem and train a Convolution Neural Network (CNN) on a carefully constructed tag vocabulary. Our proposed technique first extracts key frames from a movie and applies the trained classifier on the key frames. The predictions from the classifier are assigned scores and are filtered based on their relative strengths to generate a compact set of most relevant key tags. We performed a rigorous subjective evaluation of our proposed technique for a wide variety of movies with different experiments. The evaluation results presented in this paper demonstrate that our proposed approach can efficiently extract the key tags of a movie with a good accuracy

Aktivitas Antivirus Simian Retrovirus Serotype-2 (SRV-2) dari Ekstrak Meniran (Phyllanthus Niruri) dan Temu Lawak (Curcuma Xanthorrhiza)

Telah diteliti aktivitas antivirus dari ekstrak Meniran (Phyllanthus niruri) dan Temu Lawak (Curcuma xanthorrhiza) terhadap Simian Retrovirus Serotipe-2 (SRV-2). SRV-2 adalah virus penyebab penyakit penurunan kekebalan tubuh pada monyet jenis Macaca (K/SAIDS). SRV-2 berspektrum luas, tidak hanya menyerang sel-sel limfoid tetapi juga sel-sel tubuh lainnya. SRV dapat ditemukan pada berbagai jaringan tubuh dan organ monyet melalui metode polymerase chain reaction (PCR). Daun Meniran dan rimpang Temu Lawak diekstraksi dengan etanol lalu dipekatkan dalam alat penguap-putar. Uji morfologi sel digunakan untuk mempelajari daya toksisitas ekstrak terhadap sel. Konsentrasi ekstrak 100 ppm, 250 ppm, dan 500 ppm ditambahkan pada kultur sel A549 yang telah diinfeksi SRV-2. Aktivitas antivirus dari ekstrak dideteksi dengan teknik Real-Time PCR. Aktivitas antivirus ditentukan berdasarkan cycle threshold (Ct) dari supernatan kultur sel A549 yang diinfeksi SRV-2. Nilai Ct dari supernatan tidak terdeteksi karena jumlah virus terlalu sedikit sebagai akibat dari aktivitas antivirus yang berhasil menekan pertumbuhan virus